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Efficient structural reliability methods considering incomplete knowledge of random variable distributions

机译:考虑随机变量分布不完全知识的有效结构可靠性方法

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摘要

The determination of an exact distribution function of a random phenomena is not possible using a limited number of observations. Therefore, in the present paper the stochastic properties of a random variable are assumed as uncertain quantities and instead of predefined distribution types the maximum entropy distribution is used. Efficient methods for a reliability analysis considering these uncertain stochastic parameters are presented. Based on approximation strategies this extended analysis requires no additional limit state function evaluations. Later, variance based sensitivity measures are used to evaluate the contribution of the uncertainty of each stochastic parameter to the total variation of the failure probability.
机译:使用有限数量的观察结果是不可能确定随机现象的精确分布函数的。因此,在本文中,随机变量的随机属性被假定为不确定量,并且使用最大熵分布代替预定义的分布类型。提出了考虑这些不确定的随机参数的可靠性分析的有效方法。基于近似策略,这种扩展的分析不需要其他极限状态函数评估。后来,基于方差的敏感度度量用于评估每个随机参数的不确定性对故障概率总变化的贡献。

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